• The Journal of the Korea Contents Association
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• v.17 no.10
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• pp.343-359
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• 2017

This study aims to analyze the government accounting system of South Korea on the institutional complex and institutional congruence of new institutional theory and suggests policy reform for the system. I researched the literatures on the national and local accounting system and compiled research materials from the Ministry of Strategy and Finance, the Ministry of Interior and Safety, the Board of Audit and Inspection, and Government Accounting and Finance Statistics Center websites. Analysis showed that the government accounting system consists of various elements in institutional complex and the congruence level of national and local accounting system of South Korea is low in production, disclosure, and application of information. The suggestions of this study include: introducing accounting position recruitment, adopting government audit system, and improving cooperation between national accounting organizations and local accounting organizations for reliable information production; disclosing real time information and revealing information linking national and local accounting for transparent information disclosure; educating information user, providing accurate cost and available financial analysis indicators, introducing chief financial officer, and expanding range of consolidated national financial statements for information application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4509-4514
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• 2010

In this thesis, the effect of switch maintenance improvement is confirmed after testing and operating the switch monitoring system that were researched and developed originally in order to improve method of electric switch maintenance. However, as in an automatic interlocking station where a ground crew was not placed, repair and inspection could not be carried out until the maintenance person comes in case of switch problems or maintenance. In order to improve this issue, control module was installed in a monitoring system which can communicate through a data radio to a remote computer. Thus, the monitoring device can receive control information which a remote computer commands during the operation of switches. Afterward, it shows information on the real-time status of swith, in particular, anomaly situation through user interface after the switch is operated. By improving performance of the monitoring system in this way which can be managed and controled at a remote place, the prompt countermeasure system in case of disruption will be built and as a result, efficiency and convenience of maintenance improvement will be expected to increase.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.30
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• pp.145-174
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• 2006

An anti-dumping has become the trade policy of choice for developing countries as well as advanced countries, hence it is the impending issue to the export-oriented countries including Korea. After colligating the analysis on the trade and industrial policy between Korea and China as well as the analysis on the preceding research, the main reasons of anti-dumping were selected as followings; an unemployment rate, real GDP growth rate and consumer price increase as internal factors, and trade balance, regional coefficient and trade specification index as external factors. Then, the research on how the above seven variable factors can affect the number of anti-dumping measures was accomplished. For the empirical analysis, the above information was used after reorganizing them by on the quarterly basis. Through the use of the correlation analysis, backward elimination of multiple regression analysis model and time-series analysis, it has appeared that the unemployment rate appeared to be the most important factors of anti-dumping measures in addition to the increase rate of trade balance. The variable such as the unemployment rate is uncontrollable for us, so it is appropriate to establish and operate an preemptive monitoring system based on the increasing rate of the amount of export and increasing rate of trade surplus.

• Journal of Sensor Science and Technology
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• v.23 no.2
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• pp.99-104
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• 2014

Sensor arrays based on chemical sensors produce multidimensional patterns of data that may be used discriminate between different chemicals. For the human observer, visualization of multidimensional data is difficult, since the eye and brain process visual information in two or three dimensions. To devise a simple means of data inspection from the response of sensor arrays, PCA (Principal Component Analysis) or Sammon's nonlinear mapping technique can be applied. The PCA, which is a well-known statistical method and widely used in data analysis, has disadvantages including data distortion and the axes for plotting the dimensionally reduced data have no physical meaning in terms of how different one cluster is from another. In this paper, we have investigated two techniques and proposed a combination technique of PCA and nonlinear Sammom mapping for visualization of multidimensional patterns to two dimensions using data sets from odor sensing system. We conclude the combination technique has shown more advantages comparing with the PCA and Sammon nonlinear technique individually.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.4
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• pp.372-376
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• 2008

We report experimental results on the correlations between welding penetration depth and the frequencies of the radiation from the welding pool. Various welding samples such as SUS304, brass, SUS316, etc. have been investigated with 2 kW CW Nd:YAG laser welding machine. The radiation signals from the plume generated by the interactions between the welding sample and laser with respect to the defocusing length was measured with fiber system collecting the plume signal. Analysis of the frequencies by using fast Fourier transform (FFT) shows that the penetration depth is deep as plume signal frequencies are low, shallow penetration depth for high frequencies. Frequencies up to 250 Hz for obtained signals can be analyzed with the discrete FFT. This is the useful method fur closed loop control of the laser power with respect to the welding penetration depth and is used for real time inspection of the welding quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.959-979
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• 2024

Rice pest identification is essential in modern agriculture for the health of rice crops. As global rice consumption rises, yields and quality must be maintained. Various methodologies were employed to identify pests, encompassing sensor-based technologies, deep learning, and remote sensing models. Visual inspection by professionals and farmers remains essential, but integrating technology such as satellites, IoT-based sensors, and drones enhances efficiency and accuracy. A computer vision system processes images to detect pests automatically. It gives real-time data for proactive and targeted pest management. With this motive in mind, this research provides a novel farmland fertility algorithm with a deep learning-based automated rice pest detection and classification (FFADL-ARPDC) technique. The FFADL-ARPDC approach classifies rice pests from rice plant images. Before processing, FFADL-ARPDC removes noise and enhances contrast using bilateral filtering (BF). Additionally, rice crop images are processed using the NASNetLarge deep learning architecture to extract image features. The FFA is used for hyperparameter tweaking to optimise the model performance of the NASNetLarge, which aids in enhancing classification performance. Using an Elman recurrent neural network (ERNN), the model accurately categorises 14 types of pests. The FFADL-ARPDC approach is thoroughly evaluated using a benchmark dataset available in the public repository. With an accuracy of 97.58, the FFADL-ARPDC model exceeds existing pest detection methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1301-1316
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• 2024

In modern warfare, missiles play a pivotal role but typically spend the majority of their lifecycle in long-term storage or standby mode, making it difficult to detect failures. Preemptive detection of missiles that will fail is crucial to preventing severe consequences, including safety hazards and mission failures. This study proposes a contamination-based stacking ensemble model, employing the local outlier factor (LOF), to detect such missiles. The proposed model creates multiple base LOF models with different contamination values and combines their anomaly scores to achieve a robust anomaly detection. A comparative performance analysis was conducted between the proposed model and the traditional single LOF model, using production-related inspection data from missiles deployed in the military. The experimental results showed that, with the contamination parameter set to 0.1, the proposed model exhibited an increase of approximately 22 percentage points in accuracy and 71 percentage points in F1-score compared to the single LOF model. This approach enables the preemptive identification of potential failures, undetectable through traditional statistical quality control methods. Consequently, it contributes to lower missile failure rates in real battlefield scenarios, leading to significant time and cost savings in the military industry.

• Annual Conference of KIPS
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• 2024.10a
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• pp.626-629
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• 2024

AI-based image detection technology offers a promising solution for identifying defects in car doors, significantly improving efficiency compared to traditional human inspections. This paper introduces an advanced automatic defect detection system utilizing camera-recorded datasets and trained models to identify defects in aluminum car doors. Unlike previous models focused on aluminum castings, this is the first application specifically targeting car doors. Despite progress in defect detection research, challenges such as data imbalance, complex defect characteristics, and limited research on aluminum car doors persist. To address these issues, we propose the LKADenseNet201 model, enhancing the DenseNet201 architecture with a large kernel attention mechanism.While doing this, we focus on 3 important issues: image augmentation, channel attention and model evaluation.Our image processing process mainly include image augmentation. With image augmentation, we aimed to make data diversity suitable for the real world by obtaining data from different angles and to eliminate the imbalance between defect and normal images. This improvement boosts the model's ability to perceive contextual features and increases computational efficiency, essential for detailed spatial understanding and time-critical tasks. Our approach not only enhances operator efficiency but also moves towards automating the inspection process.

• Korean Journal of Oriental Medicine
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• v.17 no.2
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• pp.115-120
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• 2011

Objectives : The purpose of this study is to develop an apparatus which can take a facial image by self-operated capturing technique. The user can obtain one's facial image immediately after adjusting facial tilt and focusing distance. The system has been designed for classifying Sasang typology based on facial image. Methods : The system is composed of a Webcam, one-way glass mirror and mini LCD. The Webcam takes a facial image which is displayed on the mini LCD. Then the user can see and adjust to the right position in the real time through the image mirror-reflected from the mini LCD. The optical sensor is used to estimate the proper focusing distance. To verify the performance of the system, 11 characteristic points on the facial image are used and compared with high performance DSLR camera(D700) by applying the coefficient of variance and Bland-Altman Plot. Results : The developed system and D700 show enough agreement with the small coefficient of variance to analyse constitutional types with a facial im mage. However, the result of Bland-Altman plot shows that the width parameters have distortions owing to short focusing distance. Conclusions : The system is expected to be utilized on u-healthcare services for home environment after improving the distortion in the width parameters.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.3
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• pp.275-281
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• 2004

Socket weldment used to change the flow direction of fluid nay have flaws such as lack of fusion and cracks. Liquid penetrant testing or Radiography testing have been applied as NDT methods for flaw detection of the socket weldment. But it is difficult to detect the flaw inside of the socket weldment with these methods. In order to inspect the flaws inside the socket weldment, a ultrasonic testing method is established and a ultrasonic transducer and automated ultrasonic testing system are developed for the inspection. The automated ultrasonic testing system is based on the portable personal computer and operated by the program based Windows 98 or 2000. The system has a pulser/receiver, 100MHz high speed A/D board, and basic functions of ultrasonic flaw detector using the program. For the automated testing, motion controller board of ISA interface type is developed to control the 4-axis scanner and a real time iC-scan image of the automated testing is displayed on the monitor. A flaws with the size of less than 1mm in depth are evaluated smaller than its actual site in the testing, but the flaws larger than 1mm appear larger than its actual size on the contrary. This tendency is shown to be increasing as the flaw size increases. h reliable and objective testing results are obtained with the developed system, so that it is expected that it can contribute to safety management and detection of repair position of pipe lines of nuclear power plants and chemical plants.